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https://github.com/invoke-ai/InvokeAI
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enable --hires to use k* samplers
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@ -78,26 +78,14 @@ class Txt2Img2Img(Generator):
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x = self.get_noise(width,height,False)
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# Other samplers not supported yet, so ignore previous sampler
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if not isinstance(sampler,DDIMSampler):
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print(
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f"\n>> Sampler '{sampler.__class__.__name__}' is not yet supported for img2img. Using DDIM sampler"
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)
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img_sampler = DDIMSampler(self.model, device=self.model.device)
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img_sampler.make_schedule(
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ddim_num_steps=steps, ddim_eta=ddim_eta, verbose=False
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)
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else:
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img_sampler = sampler
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z_enc = img_sampler.stochastic_encode(
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z_enc = sampler.stochastic_encode(
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samples,
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torch.tensor([t_enc]).to(self.model.device),
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noise=x
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)
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# decode it
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samples = img_sampler.decode(
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samples = sampler.decode(
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z_enc,
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c,
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t_enc,
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